Seminar: Education Leadership Data Analytics
posted by Faculty of Education for HKU and Public
Event Type: Public Lecture/Forum/Seminar/Workshop/Conference/Symposium
Event Nature: Education
Education Leadership Data Analytics: Using Big Data Visual and Education Analytics to Inform Evidence-Based Decision Making in Schools
Alex J. Bowers
Associate Professor of Education Leadership, Teachers College
Columbia University, New York
June 6, 2017 (Tuesday)
12:45 – 14:00
Room 408-410, Meng Wah Complex, HKU
(Chair: Dr CY Tan)
Education data analytics is an emerging domain that merges data science, education statistics and data mining, with data visualization to help school and district leaders, teachers and policymakers make better use of the data that we already collect in schools. These types of data include traditional types of school data such as grades, test scores, discipline reports and attendance, as well as more recent innovations in personalized learning and learning management systems. Yet there are few analytics and tools that help to directly inform school and system leader decision making through leveraging these recent innovations. In this presentation, Alex J. Bowers will discuss the emerging domain of what he terms “Education Leadership Data Analytics”, in which data science and big data analytic strategies can help inform organization and leadership decision making through evidence-based improvement cycles and early warning systems. This presentation will focus on determining empirically similar longitudinal and cross-sectional patterns of districts, schools and students, through applying time-nested mixture modeling, latent class analysis and visual data analytics to issues of K-12 school pattern identification and improvement.
|Venue||Room 408-410, Meng Wah Complex, HKU|
Registration is open from 08/05/2017 17:00(HKT) to 06/06/2017 12:00(HKT) on a first-come-first-served basis.
* Registration is now closed.
Should you have any enquiries, please feel free to contact Kitty Chow by email at firstname.lastname@example.org